About the Company
Our client is a large healthcare organisation that is heavily investing in its data technologies. As part of this strategy they are seeking talent within their data and AI team in London
About the Job
Job purpose
To use statistical analysis, data science and machine-learning techniques to analyse complex healthcare data and generate actionable insights that support clinical services, operational planning, population health and organisational decision-making.
Key responsibilities
Analyse large and complex healthcare datasets from both external and internal sources.
Develop statistical and machine-learning models to answer business, operational and clinical questions.
Clean, transform and integrate data from multiple sources.
Develop reproducible analytical pipelines and maintain appropriate documentation.
Identify trends, patterns, risks and opportunities within healthcare data.
Communicate analytical findings clearly to clinical, operational and senior stakeholders.
Develop dashboards, reports and data visualisations where appropriate.
Evaluate the performance and limitations of analytical and predictive models.
Apply appropriate data-quality, information-governance and confidentiality standards.
Work collaboratively with analysts, clinicians, statisticians, engineers, researchers and operational teams.
Contribute to the development of data science standards, methods and best practice.
Support the evaluation of new analytical approaches and technologies.
Present findings to both technical and non-technical audiences.
Requirements
Essential skills and experience
Degree or equivalent experience in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering or a related quantitative discipline.
Practical experience analysing large datasets.
Strong knowledge of Python and/or R.
Good SQL skills and experience working with relational databases.
Knowledge of statistical methods and data-modelling techniques.
Experience with data cleaning, transformation and exploratory data analysis.
Experience creating effective data visualisations.
Ability to explain complex analytical results to non-technical stakeholders.
Understanding of data quality, reproducibility and analytical governance.
Ability to work independently and as part of a multidisciplinary team.
Desirable skills
Experience working with NHS, healthcare or clinical data.
Knowledge of NHS datasets such as Hospital Episode Statistics (HES), Emergency Care Data Set (ECDS), community or primary-care datasets.
Experience with machine learning and predictive modelling.
Experience with cloud platforms such as Azure, AWS or GCP.
Experience with Power BI or Tableau.
Knowledge of Git/version control and CI/CD practices.
Experience with data engineering or ETL pipelines.
Understanding of information governance, GDPR and NHS data-security requirements.
Experience evaluating models in a healthcare setting.
Knowledge of clinical terminology and healthcare pathways.
Personal attributes
Analytical and methodical approach to problem solving.
Strong communication and presentation skills.
Ability to translate business or clinical questions into analytical problems.
Commitment to data accuracy and quality.
Ability to manage competing priorities and deadlines.
Collaborative approach to working with clinical and non-clinical colleagues.
Commitment to confidentiality, equality, diversity
Typical technical stack
Python / R | SQL | Git | Power BI | Azure/AWS | Jupyter | pandas | scikit-learn | statistical modelling | data visualisation